Dense graph

Related lectures (26)

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Explores the properties of undirected and directed graphs, emphasizing connectivity and network topology modeling.

Explores the Laplacian matrix properties and consensus in continuous time.

Explores the Laplacian matrix in electric and mechanical networks, consensus, and properties of Laplacian matrices in networked control systems.

Covers sparsest cut, NP-completeness, Bougains Theorem, and concurrent flow in graphs.

Explores Laplacian operators on graphs and the model of DC microgrids.

Covers applied probability, stochastic processes, Markov chains, rejection sampling, and Bayesian inference methods.

Explores model selection challenges in causal models and the impact of local geometry on statistical inference.

Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.

Explores advanced graph coloring concepts, including planted coloring, rigidity threshold, and frozen variables in BP fixed points.